Search Results (28,192)

In recent decades, residential mobility has emerged as a fundamental interpretative key lens for understanding contemporary urban transformations, particularly in polycentric and fragmented urban contexts. Movements between different residential settings reflect economic, social and cultural changes, impacting the organisation of urban spaces, the demand for services and mobility systems. In territories characterised by dispersed settlement patterns and strong functional polarisation, these dynamics tend to promote the intensive use of private means, with consequent negative impacts on environmental sustainability, social equity and economic efficiency. In response to these critical issues, there is growing interest in sustainable mobility models based on proximity and on the integration between daily travel, access to services and the quality of public space. Within this perspective, greenways are configured as hybrid infrastructures, capable of reorganising mobility while contributing to the regeneration of urban spaces. In the Caserta area, in the Campania region, the disused route of the former Alifana railway represents a topic of great interest, both for research and planning. Its potential strategic conversion into a greenway opens a broader perspective than that so far considered at the regional level, which has mainly focused on the infrastructure dimension. The paper analyses the strengths and weaknesses of an approach limited to infrastructural mobility, proposing a comparative evaluation of project scenarios—including the non-intervention hypothesis—both through the application of the MACBETH approach and preliminary parametric estimation of construction costs, in order to emphasise the importance of integrating social and environmental benefits, as well as quality of life, into decision-making processes. Full article

After the invention of radioactive nuclear beams, studies on nuclei far from the stability line brought up many new phenomena not expected in nuclei near the stability line. Among them, neutron halos and changes in magic numbers were outstanding discoveries. To understand these phenomena, nuclear structure models needed many new developments such as the treatment of loosely bound systems and proton neutron asymmetry. One important question on the importance of the tensor interactions has been raised recently. In this review, I present evidence of tensor interactions in nucleon momentum distribution and the effects of tensor interactions on the structure of nuclei. In particular, the importance of 2p–2h configurations excited by the tensor interactions will be introduced. I show that the appearance and disappearance (blocking) of the 2p–2h configuration is responsible for the change in shell structure. I also present a recent experimental result that shows the existence of such configurations in ¹⁶O nuclei. Full article

Compared with mass spectrometry or high-performance liquid chromatography (HPLC), surface-enhanced Raman scattering (SERS) is a promising alternative technique for inspection of preservatives in food safety. However, conventional SERS substrates based on metallic nanoparticles commonly suffer from complicated fabrication processes, long processing times, and high costs. Therefore, we propose a high-density porous anodic aluminum oxide (AAO) substrate prepared by one-step anodization process combined with pore widening to increase number of SERS hotspots on template. Through a rapid one-step anodization process conducted at 25 °C, the processing time and efficiency are greatly improved compared to conventional low temperature of 0–10 °C and two-step anodization method. By lowering the anodization voltage to 20 V, a high-density porous substrate is achieved, effectively enhancing the SERS signal intensity. Furthermore, we demonstrated that SERS signal intensities are affected by multiple correlated structural factors and significantly improved by lower anodization voltage with pore widening. The analytical enhancement factor is calculated as 1.18 × 10⁵ to 1.44 × 10⁷ on an AAO substrate prepared at 20 V with pore-widening process for 1000 and 0.1 ppm p-hydroxybenzoic acid, respectively. For the preservative detection of p-hydroxybenzoic acid, a detection limit of 100 ppb is achieved by a high-density AAO substrate prepared at 20 V, which is far below the regulatory limit of 600 ppm. Full article

Recurrent meteorological droughts, projected to intensify under climate change, affect the cross-border Lima River Basin shared between Portugal and Spain, highlighting the need for robust early warning systems to support proactive water management. Within the EU-funded RISC_PLUS project—aimed at strengthening resilience to hydro-climatic risks in the cross-border Minho–Lima River Basins—this study develops a regionalised forecasting framework to evaluate meteorological drought forecast skill using precipitation forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) Seasonal Forecasting System 5 (SEAS5) for the Portuguese section of the Lima River Basin. A precipitation-only 12-month Standardized Precipitation Index (SPI12) is employed to isolate the contribution of seasonal precipitation forecasts. SPI12 is computed from hybrid 12-month accumulations combining observed monthly precipitation (October 1979 to February 2025) and SEAS5 forecasts (October 2018 to February 2025). Four hybrid configurations (1 to 6 months lead time) are evaluated: 11 obs + 1 fcst, 10 obs + 2 fcsts, 9 obs + 3 fcsts, and 6 obs + 6 fcsts. Forecast performance is assessed from October 2018 to February 2025. Deterministic SPI12 forecasts and categorical drought classifications are evaluated using regression-based metrics (e.g., Pearson correlation and RMSE) and contingency-table metrics (e.g., FAR and F1-score), across SEAS5 ensemble members, percentiles, and spread-based indicators. The 11 obs + 1 fcst configuration, particularly when using the Dry Spread (SpD; Q10 + Q25 percentiles) and the Q75 percentile, exhibits the highest skill, achieving a Pearson correlation coefficient of $r=0.97$ and an RMSE of approximately 0.17, alongside near-perfect categorical performance (POD = 1.00; FAR = 0.00), although these scores are partly conditioned by the shared observed accumulation window. Conversely, longer lead-time configurations exhibit degraded performance, with the 6 obs + 6 fcsts configuration showing weak or negative skill relative to climatology, indicating that 6-month lead forecasts should be interpreted with caution. These results demonstrate that SEAS5 precipitation forecasts can provide skilful drought predictions at lead times of several months in the Lima River Basin within the SPI12 framework. The proposed blending methodology provides a transparent benchmark and a technical basis for the early-warning system being developed under the RISC_PLUS project to support drought risk management in the Minho–Lima region and complement data-driven drought forecasting approaches. Full article

The increasing adoption of virtual reality for industrial tasks such as virtual assembly, inspection, and operator training necessitates a standardized approach for evaluating and selecting appropriate hardware. This paper addresses this need by introducing a comprehensive methodology to assess the usability of commercially widespread virtual reality headsets specifically for industrial applications with hand-held controllers. We conducted a large-scale comparative study involving five leading headsets (HTC VIVE Pro 1 and 2, HTC VIVE XR Elite, Meta Quest Pro, and Meta Quest 3) and 60 demographically balanced participants. The evaluation was based on a protocol of 15 distinct tasks designed to measure performance in near and far-field object manipulation, interaction fidelity, visual clarity, ergonomics, and long-term comfort. By combining quantitative Key Performance Indicators with subjective user feedback and rigorous inferential statistical analysis, our findings reveal significant performance disparities among the devices. The results demonstrate that, while certain headsets excel in high-precision tracking for assembly tasks, others offer superior comfort, visual quality, and ease of use for inspection and prolonged sessions. Ultimately, this study concludes that no single headset is universally superior; the optimal choice is highly task-dependent. The proposed methodology provides a robust, evidence-based framework to guide industries in making informed virtual reality hardware selections tailored to their specific needs. Full article

This study presents a systematic terahertz time-domain spectroscopy (THz-TDS) investigation of hardened cement paste, framed as a complex-optical measurement in which the real and imaginary parts of the response probe distinct microstructural attributes. Transmission-mode measurements were made on pastes with water-to-cement (w/c) ratios of 0.3, 0.4, and 0.5 at curing ages of 7, 14, 28, and 56 days. The effective refractive index, obtained from the time-domain pulse delay (7, 28, and 56 days, paired with mercury intrusion porosimetry), correlates strongly and linearly with porosity over nine porosity-paired conditions spanning 15.1–30.4% (pooled R² = 0.94, p < 0.001). In a quasi-static effective-medium framework—where the pores a re far smaller than the THz wavelength—this reflects the dependence of the effective permittivity on the solid volume fraction: the Bruggeman model outperforms the Maxwell–Garnett model, and all data fall within the Wiener bounds, lying close to the upper bound, indicating a continuously connected solid matrix with isolated pores. Cross-validated porosity estimation is reliable to within about ±2 percentage points (refractive-index uncertainty ±0.02–0.04). The absorption follows a power law (β ≈ 1.0–1.3) characteristic of disorder-activated vibrational absorption, in which the loss of long-range order in the amorphous C–S–H relaxes the crystalline selection rules and couples the THz field to the full vibrational density of states. The refractive index (structure-sensitive, governed by volume fraction) and the absorption (material-sensitive, governed by solid disorder; estimated loss tangent of order 0.1) thus form two complementary channels. Combining the THz-derived porosity with the Powers hydration model gives a degree of hydration consistent with literature ranges—an indirect comparison rather than direct validation. These results establish THz-TDS as a non-contact, non-ionizing technique for rapid porosity estimation and hydration assessment of cementitious materials. Full article

In linear regression, a point predictor ${\widehat{Y}}_{\mathrm{f}}$ of a future response $Y_{\mathrm{f}}$ associated with a regressor value of interest ${\underline{x}}_{\mathrm{f}}$ can easily be constructed. Since ${\widehat{Y}}_{\mathrm{f}}$ will always incur a prediction error, it is desirable to accompany the point predictor by a prediction interval, say $C\left({\underline{x}}_{\mathrm{f}}\right)$, that will contain the target $Y_{\mathrm{f}}$ with a pre-specified high probability, e.g., 90%. An estimated prediction interval, say $\widehat{C}\left({\underline{x}}_{\mathrm{f}}\right)$, is called pertinent if its construction incorporates the variability of all estimators that are employed in the prediction problem. So far, pertinent prediction intervals have only been constructed via some form of bootstrap. However, resampling can be quite computationally expensive since the estimation/prediction problem has to be re-calculated on a large number of pseudo-scatterplots, each having the same sample size as the original one. The paper at hand proposes a short-cut that directly employs the asymptotic normal distribution of relevant estimators—as opposed to a bootstrap histogram—in order to capture their variability. The resulting prediction interval achieves pertinence without full-scale resampling, thus offering computational savings of orders of magnitude. Full article

Long and narrow shielded confined spaces, represented by traffic tunnels and underground utility tunnels, constitute critical application scenarios for indoor and underground positioning services. Despite their relatively simple geometric configurations, such environments suffer from severe spatial distortion of geometric dilution of precision (GDOP). Coupled with pervasive low-elevation signal propagation and intensive multipath reflection effects, conventional BeiDou Navigation Satellite System (BDS) positioning services are unable to provide continuous and reliable coverage in these scenarios. To date, existing research on high-precision pseudolite positioning for narrow confined spaces remains largely confined to theoretical analysis and laboratory experimental verification, while systematic studies on application-oriented signal atlas feature network design are significantly insufficient, forming a prominent gap that restricts the practical engineering deployment of relevant technologies. To address the aforementioned technical bottlenecks, this paper proposes a novel BDS pseudolite signal atlas network design method to improve the continuity, stability and comprehensive positioning performance in spatially distorted narrow shielded environments. Field vehicular tests were carried out in actual engineering tunnels and underground utility tunnels to systematically analyze the variation characteristics of raw BDS pseudolite observation data, including pseudorange, carrier phase, carrier-to-noise ratio (C/N₀) and Doppler shift. The test results verified that kinematic Doppler parameters exhibited outstanding stability in complex shielded environments with strong multipath interference. On this basis, a spatial feature model based on kinematic Doppler measurements was constructed, and wavelet denoising technology was adopted to extract effective typical spatial feature parameters. Combined with the deterministic one-to-one mapping relationship between Doppler peak characteristics and spatial positions, a multi-peak kinematic Doppler atlas was established, which eliminates the dependence on pre-deployment data collection, dedicated database construction and offline model training. Furthermore, comprehensively considering multi-dimensional constraints such as spatial environment scale, carrier dynamic characteristics and terminal output rate, the atlas network scheme was optimized to achieve a balanced trade-off among positioning detection accuracy, absolute positioning precision and suppression of the pseudolite near-far effect. Comparative experimental results demonstrate that the proposed BDS pseudolite atlas network effectively resolves the inherent GNSS positioning difficulty in long and narrow shielded spaces. Benefiting from the rational spectral peak configuration strategy, the system can satisfy the continuous and stable positioning requirements of multiple carrier types including motor vehicles and railway locomotives under variable motion speeds and terminal output rates. This study provides a robust and feasible technical solution for high-precision BDS positioning services in long and narrow shielded confined spaces, and holds favorable engineering application prospects for underground navigation scenarios. Full article

This study presents a reusable adjoint-octree multilevel fast multipole algorithm (MLFMA) for full-wave radar scattering analysis of multi-state unmanned aerial vehicle (UAV) formations. The method is motivated by remote-sensing applications in which dense angular sampling or long motion sequences are required for physically reliable signature generation. Instead of rebuilding a global octree for the full formation at every motion state, the proposed approach assigns each sub-target an independent target-attached local octree that translates and rotates with the rigid body. This preserves mesh–cell affiliation in the body-fixed frame and separates the system operator into a state-invariant intra-target near-field component and a state-dependent inter-target far-field component. Consequently, near-field matrices and sparse approximate inverse preconditioners are assembled once and reused throughout the state sequence, while only inter-target far-field coupling terms are updated. The method is evaluated for six representative UAV formations at 3.5 GHz using monostatic radar cross section (RCS) over a full azimuth sweep. Across all tested formations, the proposed solver reproduces the RCS behavior of conventional MLFMA while substantially reducing computational cost. For Formation A, the center-state total time decreases from 251.4 s to 66.06 s; for Formation C, it decreases from 470.95 s to 76.06 s. Over 100-state sequences, the resulting acceleration reaches approximately 11.8-fold and 15.2-fold, respectively. Jitter-envelope analysis further shows that orientation perturbation produces stronger signature uncertainty than planar displacement. The proposed framework therefore provides an efficient and physically consistent forward solver for radar remote-sensing studies of cooperative UAV formations. Full article

Accurate rainfall estimates are essential for managing water resources and planning for climate risks in semi-arid regions, yet long-term gauge networks in these environments are often extremely limited. In this study, we evaluate three widely used multi-source precipitation datasets—CHIRPS, IMERG, and ERA5-Land—against long-term observations from Ed Dueim and Kosti, the two main reference stations in White Nile State, central Sudan. The assessment covers monthly and annual scales across each product’s available record (1952–2022) and uses a broad set of metrics, including Pearson and Spearman correlations, NSE, KGE, RMSE, MAE, percent bias, and categorical detection scores (POD, FAR, CSI). All three datasets capture the region’s single-peak June–October monsoon pattern, but their accuracy differs sharply when it comes to rainfall amounts and year-to-year variability. CHIRPS performs best overall, with the strongest monthly efficiency scores of any product and a consistent, operationally correctable dry bias of 5–13%. IMERG shows strong monthly correlations but consistently overestimates rainfall by 25–42%, which leads to unreliable annual totals. ERA5-Land performs worst across nearly all metrics, with monthly NSE near or below zero, and frequent false alarms during the dry season. Taken together, the evidence points to CHIRPS as the most reliable dataset for routine hydro-climatic monitoring in White Nile State, while IMERG and ERA5-Land may still be useful in more specialized or time-specific applications. Full article

The growing penetration of renewable generation changes both producers’ marginal-cost and electricity-market price formation. This paper develops a mean field game model to examine how heterogeneous generators adjust marginal generation costs through renewable-oriented investment and how these decisions feed back into bid-stack clearing. Each generator controls the drift of its marginal cost, while the clearing price is determined by a demand-dependent quantile of the population cost distribution. The model leads to a coupled system with a non-local payoff. Simulations show that cost-reduction investment shifts the marginal-cost distribution toward lower-cost regions, but the widening distribution indicates heterogeneous effects. Generators below and close to the clearing margin have stronger incentives to reduce costs, whereas high-cost generators far above the margin face weaker incentives. These results suggest that market competition can support renewable-oriented cost reduction, but complementary policies may be needed for high-cost generators. Full article

Hands-free command interfaces are essential for users who cannot reliably operate joysticks or upper-limb myoelectric control. Neck–shoulder surface electromyography (sEMG) is a promising alternative; however, performance is often reported using window-level validation which can overestimate accuracy due to overlap and trial leakage, and false-trigger behavior is not always quantified when an idle REST state is included. This pilot study presents a motion-capture (MoCap)-referenced decoding framework that uses four bilateral upper trapezius (UT) and sternocleidomastoid (SCM) sEMG channels with integrated inertial measurement units (IMUs). Optical MoCap was used as an external kinematic reference to support baseline-posture assessment and movement-execution quality control. Seven commands were decoded (shrug L/R, double shrug, rotation L/R, rotation + shrug L/R). To enable an eight-class formulation, a REST class was defined using low-activity segments extracted from baseline recordings and included in the evaluation. Computationally efficient time-domain sEMG features, pattern/symmetry descriptors, and baseline-referenced IMU kinematics (including an SCM yaw-range indicator) were classified using linear discriminant analysis (LDA), k-nearest neighbors (kNN), and linear support vector machine (SVM), evaluated using within-subject testing, trial-wise grouped cross-validation, and leave-one-subject-out (LOSO) testing. Across six participants, within-subject mean best-per-subject accuracy was 96.02% (seven-class) and 96.35% (eight-class); and pooled trial-wise accuracy reached 92.1% and 90.5%, respectively. Under LOSO, best-configuration accuracy decreased to 60.4% and 63.8% for the seven-class and eight-class formulations, respectively. Across the top LOSO configurations, REST FAR ranged from approximately 9.8% to 25.6%. These findings demonstrate controlled offline pilot feasibility and quantify key generalization and REST false-activation trade-offs, providing a foundation for future validation in larger, more diverse, and clinically relevant populations. Full article

Digital twin (DT) technology has expanded far beyond its industrial origins, increasingly finding application across environmental and territorial domains. This review provides a structured mapping of DT deployments at environmental and territorial scales over the period 2020–2025, examining 117 peer-reviewed publications (109 applied studies and 8 review articles) through a structured 16-parameter classification framework. The review traces three major conceptual shifts in the DT paradigm: from industrial assets to living entities, from discrete systems to Earth-scale representations, and from closed deterministic models to ecological and systemic frameworks, as reflected in the emergence of ecological digital twins (EcoDTs), environmental digital twins (EDTs), and territorial digital twin (TDT) definitions. The results reveal a clear growth trajectory in DT applications across themes, with urban systems as the most consolidated application domain, and progressive diversification into marine, coastal, forestry, river/lake, and Earth system applications from 2022 onward. Institutional actors dominate production in this space, aligned with European flagship initiatives such as Destination Earth (DestinE) and the European Digital Twin of the Ocean (EDITO). The findings position and expand the notion of territorial digital twins as an evolving paradigm, underscoring both the momentum generated by EU digital and environmental policy and the need for integrated tools to answer and respond to key environmental challenges. Full article

Artificial-source frequency-domain electromagnetic methods are important tools for deep mineral exploration and concealed geological structure detection. Apparent resistivity is a key parameter linking measured electromagnetic fields to the interpretation of subsurface electrical structures, and its calculation method directly affects geological interpretation and engineering applicability. Although substantial efforts have been devoted to the theoretical development, data processing, and practical application of different apparent resistivity formulations, most previous studies have focused on the analysis and improvement of a single method. Systematic comparisons of the main apparent resistivity formulations under unified conditions remain limited, particularly in terms of deep basement characterization, anti-interference performance, and engineering applicability. To fill this gap, this study systematically compares the $E-E_x$ wide-field apparent resistivity, the $E-E_x$ far-zone apparent resistivity, and the $E-Z_{xy}$ Cagniard apparent resistivity. Through theoretical derivation, forward modeling of typical one-dimensional models, and field verification, the differences among these three formulations in geological characterization, anti-interference capability, and engineering applicability are analyzed, with the aim of clarifying their applicable boundaries and selection principles for artificial-source frequency-domain electromagnetic exploration. Full article

Coccocypselum lanceolatum is a tropical, perennial, creeping, herbaceous C3 plant species that is found in deeply shaded humid forests. This species has potential for medicinal and culinary uses. Knowledge about this species and other herbaceous Rubiaceae is confined to phytocoenological and morpho-anatomical studies. Here, it was hypothesized that (1) leaf gas exchange dynamics over a one-year period in C. lanceolatum are related to light conditions, phenology and environmental seasonal changes; (2) photosynthetic performance is focused on enhanced carbon gains through a high leaf net assimilation rate (A_net) relative to light availability, a low dark respiration rate (R_d) and a light compensation point (LCP); and (3) these parameters will vary over leaf age. The photosynthetic photon flux density (PPFD), characterizing the growth and development of C. lanceolatum, was reduced to 4–11% of incoming light in the open area, while the red-to-far-red light ratio (R:FR) was reduced from 1.15 to mean diurnal values of 0.45–0.81, depending on forest canopy dynamics. Leaf gas exchange parameters [A_net, stomatal conductance (g_s), leaf transpiration (E), and intrinsic water use efficiency (iWUE)] were observed over a one-year period. A_net, g_s, and E were correlated with energy factors (PPFD and air temperature) during vegetative growth, while only iWUE showed a correlation with leaf gas exchange parameters during blooming and fruiting, indicating that seasonality and phenology were additional drivers of leaf gas exchange. As a deep-shade forest species, C. lanceolatum displayed low iWUE (3–21 μmol m⁻² s⁻¹) and was adapted to maximize carbon gain and prioritize high g_s rather than water economy. The extremely low LCP (4.2 μmol m⁻² s⁻¹), low R_d (0.2 to 0.43 μmol m⁻² s⁻¹), maximum net photosynthesis (A_max, 5 μmol m⁻² s⁻¹), and apparent quantum efficiency of CO₂ assimilation (Φ of 0.04 µmol µmol⁻¹) were adaptational traits of this species for low light. Finally, the A_net, g_s, E, iWUE, gross photosynthesis under light saturation, R_d, LCP, and light saturation point values were different when comparing young and adult leaves. The ecophysiological responses over a one-year period shown here could assist in the success of C. lanceolatum as a sustainable soil-cover plant in shaded areas. Full article